Read in the data
sf_rent <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-07-05/rent.csv')
glimpse(sf_rent)
## Rows: 200,796
## Columns: 17
## $ post_id <chr> "pre2013_134138", "pre2013_135669", "pre2013_127127", "pre…
## $ date <dbl> 20050111, 20050126, 20041017, 20120601, 20041021, 20060411…
## $ year <dbl> 2005, 2005, 2004, 2012, 2004, 2006, 2007, 2017, 2009, 2006…
## $ nhood <chr> "alameda", "alameda", "alameda", "alameda", "alameda", "al…
## $ city <chr> "alameda", "alameda", "alameda", "alameda", "alameda", "al…
## $ county <chr> "alameda", "alameda", "alameda", "alameda", "alameda", "al…
## $ price <dbl> 1250, 1295, 1100, 1425, 890, 825, 1500, 2925, 450, 1395, 1…
## $ beds <dbl> 2, 2, 2, 1, 1, 1, 1, 3, NA, 2, 2, 5, 4, 0, 4, 1, 3, 3, 1, …
## $ baths <dbl> 2, NA, NA, NA, NA, NA, 1, NA, 1, NA, NA, NA, 3, NA, NA, NA…
## $ sqft <dbl> NA, NA, NA, 735, NA, NA, NA, NA, NA, NA, NA, 2581, 1756, N…
## $ room_in_apt <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ address <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ lat <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 37.53494, …
## $ lon <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ title <chr> "$1250 / 2br - 2BR/2BA 1145 ALAMEDA DE LAS PULGAS", "$12…
## $ descr <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ details <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "<p class=…
## # A tibble: 6 × 17
## post_id date year nhood city county price beds baths sqft room_…¹
## <chr> <dbl> <dbl> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 pre2013_134138 2.01e7 2005 alam… alam… alame… 1250 2 2 NA 0
## 2 pre2013_135669 2.01e7 2005 alam… alam… alame… 1295 2 NA NA 0
## 3 pre2013_127127 2.00e7 2004 alam… alam… alame… 1100 2 NA NA 0
## 4 pre2013_68671 2.01e7 2012 alam… alam… alame… 1425 1 NA 735 0
## 5 pre2013_127580 2.00e7 2004 alam… alam… alame… 890 1 NA NA 0
## 6 pre2013_152345 2.01e7 2006 alam… alam… alame… 825 1 NA NA 0
## # … with 6 more variables: address <chr>, lat <dbl>, lon <dbl>, title <chr>,
## # descr <chr>, details <chr>, and abbreviated variable name ¹​room_in_apt
# Get data for counties and filter to keep just the counties in California
CA<-map_data("county") %>%
filter(region == "california")
head(CA)
## long lat group order region subregion
## 1 -121.4785 37.48290 157 6965 california alameda
## 2 -121.5129 37.48290 157 6966 california alameda
## 3 -121.8853 37.48290 157 6967 california alameda
## 4 -121.8968 37.46571 157 6968 california alameda
## 5 -121.9254 37.45998 157 6969 california alameda
## 6 -121.9483 37.47717 157 6970 california alameda